User:VirtMorph/en/Cinematic Rendering

= Cinematic Rendering = Siemens Healthineers advanced Cinematic Rendering is a volume rendering technology. Cinematic Rendering is an image processing technique applied in medical diagnostics to create three-dimensional, photorealistic images of cross-sectional data, such as computed-tomography, or magnetic resonance imaging. In 2017, Klaus Engel, Franz Fellner and Robert Schneider were nominated for the German Future Prize for their interdisciplinary collaboration on Cinematic Rendering.

Technology
Based on the volumetric Monte-Carlo Path Tracing algorithm, Cinematic Rendering traces hundreds to thousands of light path per pixel through the data generated by a virtual camera. The light input is averaged along these path and transported from high dynamic range images back to the virtual camera sensor. The scattering, absorption and emission is then simulated along the optical paths by means of the interaction between the light and the volumetric data, resulting in vivid, realistic anatomical images of similar image quality similar to CGI sequences used in the film industry.

Medical Applications
Approved for use in the medical field, cinematic rendering is being applied to a range of different areas that include radiology (to supplement available cross-sectional images), surgery (to plan preoperative procedures, such as oral and maxillofacial surgery, trauma surgery and orthopedics), as well as cardiovascular surgery and interventional radiology. The system can also be used across disciplines to, for example, train post-graduate medical personnel, as well as support patient education and interdisciplinary clinical meetings (such as tumor boards).

Applications in Medical Education
Cinematic rendering technology is currently applied as a virtual educational method at specialized facilities, institutions, and centers to teach the subject of anatomy to both medical students and other healthcare professions, for example, at the JKU Faculty of Medicine at the Johannes Kepler University Linz, and for post-graduate programs in clinical areas as well as medical assistant professions.

Weblinks
German Future Prize 2017 – Team 1

Ars Electronica Futurelab: Cinematic Anatomy x Deep Space

References and Resources
Fellner, F.: Introducing Cinematic Rendering: A Novel Technique for Post-Processing Medical Imaging Data. Journal of Biomedical Science and Engineering, 2016, 9, 170-175. doi:10.4236/jbise.2016.93013

Eid, M. et al.: Cinematic Rendering in CT: A Novel, Lifelike 3D Visualization Technique. American Journal of Roentgenology, 2017, 209, doi:10.2214/AJR.17.17850

Dappa, E., et al.: Cinematic rendering – an alternative to volume rendering for 3D computed tomography imaging Insights Imaging, 2016, 7, doi: 10.4236/jbise.2016.93013

Li, K., et al.: Value of the Cinematic Rendering From Volumetric Computed Tomography Data in Evaluating the Relationship Between Deep Soft Tissue Sarcomas of the Extremities and Adjacent Major Vessels: A Preliminary Study. Journal of Computer Assisted Tomography, 2019, 43, doi:10.1097/RCT.0000000000000852

Moser, S.E.: Cinematic Rendering: Körperkino für das Tumorboard. Deutsches Ärzteblatt, 2017, 114, 35-36

Fellner F., et al.: Virtual Anatomy: The Dissecting Theatre of the Future—Implementation of Cinematic Rendering in a Large 8 K High-Resolution Projection Environment. Journal of Biomedical Science and Engineering, 2017, 10, doi:10.4236/jbise.2017.108028

Binder J., et al.: Cinematic Rendering in Anatomy: A Crossover Study Comparing a Novel 3D Reconstruction Technique to Conventional Computed Tomography. Anatomical Sciences Education, 2021, 14, doi:10.1002/ase.1989

Niedermair, J., et al.: On the added benefit of virtual anatomy for dissection-based skills. Anatomical Sciences Education, 2023, 16, doi:10.1002/ase.2234